Urban air quality is one of the main environmental concerns. The interaction between atmosphere and buildings induces complex flows within the streets and squares. This fact joint with the traffic emissions produce a heterogeneous distribution of pollutants with high gradients of concentration. The main objective of this work is to obtain high resolution maps of particle matter concentration using a CFD model so as to analyze air quality and population exposure. This study is focused on a heavily trafficked roundabout in Madrid (Fernandez Ladreda square). To achieve this objective, CFD modelling coupled with detailed emissions of PM10 and PM2.5 and outputs from WRF meteorological mesoscale model is performed. Emissions from vehicle exhaust and particle resuspension are considered with a resolution of 5 m x 5 m. The simulated mesoscale vertical profiles of wind velocity and turbulent kinetic energy, previously checked with onsite meteorological measurements, are used as boundary conditions.  The effects of urban vegetation are modelled and moreover, the CFD modelling is improved implementing vehicle induced turbulence as a source of turbulence on the roads. Modelling results are evaluated for several periods of summer and winter by using data from experimental campaigns carried out in this zone in the framework of the TECNAIRE research project

Artíñano, Begoña

Blanco, C.

Borge García, Rafael

Díaz, Elías

Gómez-Moreno, F. J.

Martilli, Alberto

Martín, Fernando

Paz Martín, David de la

Quaassdorff, Christina Violetta

Sanchez, Beatriz

Santiago, José Luis

Vardoulakis, Sotiris

Yagüe, C.

Servicio de Coordinación de Bibliotecas de la Universidad Politécnica de Madrid

18th International Conference on 
Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes 
9-12 October 2017, Bologna, Italy
______________________________________________________________________
CFD MODELLING OF PARTICLE MATTER DISPERSION IN A REAL HOT-SPOT 
 J.L. Santiago
1
, B. Sanchez
1
, F. Martin
1
, A. Martilli
1
, C. Quaassdorff
2
, D. de la Paz
2
, R. Borge
2
, F.J. 
Gómez-Moreno
1
, E. Díaz
1
, B. Artíñano
1
, C. Yagüe
3
, C. Blanco
3
, S. Vardoulakis
4 
1
Department of Environment, CIEMAT, Madrid, Spain.
2
Department of Chemical & Environmental Engineering, Technical University of Madrid, (UPM).
3
Department of Geophysics and Meteorology, University Complutense of Madrid, Faculty of Physical 
Science. 
4
Environmental Change Department, Centre for Radiation, Chemical & Environmental Hazards, Public 
Health England, Chilton OX11 ORQ, UK.
Abstract: Urban air quality is one of the main environmental concerns. The interaction between atmosphere and 
buildings induces complex flows within the streets and squares. This fact joint with the traffic emissions produce a 
heterogeneous distribution of pollutants with strong gradients of concentration. The main objective of this work is to 
obtain high resolution maps of particle matter concentration using a Computational Fluid Dynamic (CFD) model so 
as to analyze air quality and population exposure. This study is focused on a heavily trafficked roundabout in Madrid 
(Fernandez Ladreda square). To achieve this objective, CFD modelling coupled with detailed emissions of PM10 and 
PM2.5 and outputs from WRF meteorological mesoscale model is performed. Emissions from vehicle exhaust, particle 
resuspension, pavement abrasion and brake and tire wear are considered with a horizontal resolution of 5 m x 5 m. 
The effects of urban vegetation are also modelled. Modelling results are evaluated for several periods of summer and 
winter by using data from experimental campaigns carried out in this zone in the framework of the TECNAIRE 
research project.
Key words: Coupling mesoscale-microscale models, CFD modelling, detailed traffic emissions.
INTRODUCTION
Urban air quality is one of the most important environmental challenges and the largest environmental 
health risk in Europe due to the high percentage of population that lives in cities and the high pollution 
levels there. The complex flow patterns within the urban canopy joint to the irregular traffic emissions 
along the city induce a heterogenous pollutant distribution within streets and squares. In order to capture 
these strong concentration gradients, high spatial resolution is needed. In this way, Computational Fluid 
Dynamics (CFD) models which are able to solve explicitly the complex air flow and dispersion induced 
by urban obstacles seem to be an adequate tool to study this issue. This study is focused on particle matter 
dispersion in a real urban hot-spot in Madrid (Spain). CFD modelling coupled with mesoscale model 
outputs and detailed emissions of PM10 and PM2.5 is used to obtain high resolution maps of particle matter 
concentration. The comparison of modelling results (meteorology and concentration) against data from 
experimental campaigns carried out in this zone in the framework of the TECNAIRE research project
(Borge et al., 2016) allowed us to analyze how to improve some aspects of CFD modelling. 
DESCRIPTION OF THE STUDY AREA AND EXPERIMENTAL CAMPAIGNS
The area of study is located in the south-west of Madrid city in a heavily trafficked roundabout 
(Fernandez Ladreda square) with a main road crossing under it through a tunnel (Figure 1). This location,
which presents high levels of pollution, is complex in terms of urban morphology (buildings and
vegetation), intense road traffic, interaction of emissions sources and presence of pedestrian (Borge et al., 
2016; Sanchez et al., 2017a).
596
Meteorological monitoring  
Two experimental campaigns were carried out in this zone during winter and summer 2015. This study is 
focused on two days (25th February and 6th July) which are simulated by CFD model from 6 to 18 UTC.
Atmosphere conditions were monitored in three points (Figure 1a): a) wind speed and direction were 
recorded by a meteorological station in the roof of a building (Iberdrola building) at 18 m above ground 
level (AGL), approximately and, b) micrometeorological parameters were measured by two sonic 
anemometers at 6 and 8 m AGL. The point at Iberdrola building was taken as representative of general 
meteorological conditions. 
Particulate matter concentration 
PM10 and PM2.5 concentration data were recorded from a Grimm instrument located close to sonics 
anemometers. In addition, a portable TSI DustTrak
TM
 DRX instrument was moved around the square 
measuring PM10 concentration at several points at a height of approximately 1.5 m. 
a) b)
Figure 1. Area of study. a) Real geometry. b) Numerical domain with PM10 exhaust emissions in µg m
-2 s-1. Location 
of vegetation is represented in green.
METHODOLOGY 
The main objective is to simulate particulate matter dispersion by means of CFD modelling. In order to 
improve the uncertainties of CFD modelling, accurate boundary conditions and emissions are required. 
Meteorological conditions are reproduced coupling mesoscale model outputs to CFD model and 
emissions implemented in CFD model are taken from traffic and emissions micro-simulation models (see 
details in next section). Hourly inlet wind direction is taken from meteorological station (Iberdrola
building) instead of mesoscale model outputs, however the fluctuations of wind direction during each 
hour are not considered. 
MODEL DESCRIPTIONS AND SET-UPS
Meteorological mesoscale model (WRF)
Madrid urban atmosphere at mesoscale was simulated by means of WRF (Weather Research and 
Forecasting) model (Chen et al., 2001). For winter campaign, four nested domains were simulated with 
the finest domain with a horizontal resolution of 1 km x 1 km. In vertical, the resolution of the lowest 
levels are 5 m (see details in Sanchez et al., 2017a). A multilayer urban scheme was used to simulate 
urban areas (BEP-BEM, Martilli et al. (2002) and Salamanca et al. (2010)). Similar configuration was 
used to simulate meteorological conditions of summer campaign but with a resolution of the finest 
domain of 500 m x 500 m.  
Traffic emission model 
Hourly emissions with resolution of 5 m x 5 m are computed by means of a combination of traffic and 
emissions micro-simulation models (Quaassdorff et al., 2016). In this study, PM2.5 and PM10 emissions 
from vehicle exhaust, particle resuspension, pavement abrasion and brake and tire wear are considered in 
a region of 300 m x 300 m around the square (Fig. 1b).
Meteorological station
Sonic anemometers
PM10 Measurements
597
CFD model 
The CFD model used is based on Reynolds-Averaged Navier-Stokes (RANS) equations with a Realizable 
k-ε turbulence closure. In addition, buoyancy terms are taking into account using Bousinesq’s approach 
and an equation for temperature is solved. Transport equations are solved for pollutants dispersion with a 
low Schmidt number (Sc = 0.3). The software used is STAR-CCM+ from CD-Adapco. The size of 
numerical domain is 1300 m x 1300 m x 270 m. An irregular mesh is used, where the resolution is 2 m
approximately around the square with smaller cells than 1 m close to the ground, buildings and the 
emissions zone. Further from this area the cell size progresivelly increase to 5 m. The total number of grid 
points is 8.3 10
6
 (Sanchez et la., 2017a). Unsteady CFD simulations are performed from 6UTC to 18UTC 
of 25th February and 6th July. Hourly vertical profiles of wind, temperature (T) and turbulence kinetic 
energy (TKE) obtained from WRF model in the mesoscale cell corresponding to microscale domain are 
used as inlet boundary conditions at each hour in the CFD model. The vertical profile of dissipation rate 
(ε) is computed from TKE profile as,  !" = #$
%/&'()*!"
%/+/,-.0. A radiation model is not implemented in 
the CFD model, however in order to analyze the effects of surface heat fluxes at different hours, two 
scenarios are simulated: 1) considering adiabatic the ground and buildings and 2) imposing at ground the 
surface heat flux computed at mesoscale in the whole domain by WRF at each hour (Sanchez et al., 
2017b). 
RESULTS 
Evaluation of meteorological results 
Firstly, wind speed and direction is evaluated at 18m AGL in Iberdrola building. This point could be 
considered as a measurement of the general atmospheric conditions, however for some wind directions it 
is affected by the sheltering of higher building located in the South. 
a) b)
c) d)
Figure 2. Time series at 18 m AGL of experimental data, WRF and CFD (with and without surface heat fluxes) 
results of: a) wind speed and b) wind direction for 25th February. c) wind speed and d)  wind direction for 6th July. 
Figure 2 shows that on 25th February the wind speed is understimated by WRF and CFD model. This 
indicates that the wind speed imposed at inlet in the microscale domain is lower than actual wind speed 
and thus the CFD results are influenced by this issue. On 6th July, modelling results are much closer to 
the experimental data. Hourly mean wind direction is in agreement with experimental data. From Figure 
598
3, we can observe that the CFD results fit better with measurements for 6th July due to  more accurate 
inlet conditions. For the winter day, the inlet wind speed underestimation induces an underestimation of 
the wind speed and a high underprediction of the TKE measured by the sonic anemometers. In addition, 
considering the surface heat flux (SHF) at ground improve the CFD results, especially TKE. This could 
be important for pollutant dispersion at some hours where the TKE computed without SHF is almost 0, 
for example at 8UTC of 6th July. 
a) b)
c) d)
Figure 3. Time series at sonic anemometer located at 6 m AGL of experimental data, WRF and CFD (with and 
without surface heat fluxes) results of: a) wind speed and b) turbulent kinetic energy for 25th February. c) wind speed 
and d)  turbulent kinetic energy for 6th July.
Evaluation of particulate matter concentrations 
In order to illustrate the performance of the CFD simulations of particle matter dispersion, we focus on 
8UTC of 6th July, one of the hours where experimental data are available and the meteorology (hourly 
values of wind speed and turbulence) is well captured by the CFD model. PM10 concentration is measured 
by the portable TSI DustTrak
TM
 at 10 different points during several minutes and by a GRIMM during 
this hour (see Fig. 4). In the comparison three different CFD modelling approaches are considered: 1) 
simulation without surface heat fluxes with Sc = 0.3, 2) simulation with surface heat flux at ground with 
Sc = 0.3, and 3) simulation with surface heat flux (SHF) at ground with Sc = 0.7. In the previous section, 
it is observed that meteorological measurements are better reproduced in simulations which take into 
account SHF. On the other hand, Schmidt number (Sc) is a parameter that according to flow properties 
and geometries could be in a range from 0.2 to 1.3 depending on the case. The selection of 0.3, which 
implies a greater diffusion, in this geometry is based on Sanchez et al. (2017a) in order to minimize the 
error due to processes as heat fluxes or turbulence induced by traffic that were not considered. Figure 4 
shows that the area with higher concentration are wider for simulation without SHF. The concentration 
decrease as SHF are considered, but in Fig. 5 we can observe that modelled concentration in this case are 
lower than experimental values using Sc=0.3. Since the dispersion increases by imposing the surface 
heating at ground, the rise of the Sc to 0.7 is assumed and ii improves the simulation results. Despite it all, 
the values in some points are still underestimated by CFD. This could be due to hourly mean wind 
direction is imposed at inlet, however the fluctuations of wind direction are significant during this hour. 
599
Figure 4. PM10 concentration maps at 8UTC at 1.5 m for: a) CFD with Sc=0.3, b) CFD+SHF with Sc=0.3, and c) 
CFD+SHF with Sc=0.7.
Figure 5. PM10 concentration at 8UTC in the point measurements. Vertical bars in experimental data indicates the 
maximum and minimum measured.
CONCLUSIONS AND LESSONS LEARNED 
Using WRF outputs as boundary conditions of CFD model including SHF improves microscale results. 
However, the uncertainties in the inlet boundary conditions affect the performance of CFD simulations.
Some parameters as surface heat flux in the meteorology or Schmidt number in the pollutant dispersion 
should be analyzed in detail for each case depending on processes considered in the model. These are 
preliminary conclusions and a more extensive study is necesary. 
REFERENCES 
Borge, R., Narros, A., Artínano, B., Yagüe, C., Gómez-Moreno, F.J., de la Paz, D., Roman-Cascón, C., Díaz, E., Maqueda, G., 
Sastre, M., et al., 2016: Assessment of microscale spatio-temporal variation of air pollution at an urban hotspot in Madrid 
(Spain) through an extensive field campaign. Atmospheric Environment 140, 432-445. 
Martilli, A., Clappier, A., Rotach, M.W., 2002. An urban surface exchange parameterization for mesoscale models. Boundary-Layer 
Meteorology 104 (2), 261-304. 
Quaassdorff, C., Borge, R., Perez, J., Lumbreras, J., de la Paz, D., de Andrés, J.M., 2016: Microscale traffic simulation and emission 
estimation in a heavily trafficked roundabout in madrid (Spain). Sci. Total Environ. 566, 416-427. 
Salamanca, F., Krpo, A., Martilli, A., Clappier, A., 2010: A new building energy model coupled with an urban canopy 
parameterization for urban climate simulations. Part I. Formulation, verification, and sensitivity analysis of the model. 
Theor. Appl. Climatol. 99 (3-4), 331-344. 
Sanchez, B., Santiago, J.L., Martilli, A., Martin, F., Borge, R., Quaassdorff, C., de la Paz, D., 2017a: Modelling NOx concentrations 
through CFD-RANS in an urban hot-spot using high resolution traffic emissions and meteorology from a mesoscale 
model. Atmospheric Environment, 163, 155-165. 
Sanchez, B., Santiago, J.L., Martin, F., Martilli, A., Quaassdorff, C., de la Paz, D., Borge, R., 2017b: Modelling reactive pollutants 
dispersion in an urban hot-spot in summer conditions using a CFD model coupled with meteorological mesoscale and 
chemistry-transport models. In: HARMO18 conference (H18-164), Bologna, 9-12 October, Italy.
ACKNOWLEDGEMENTS
This study has been supported by the TECNAIRE-CM research project (S2013/MAE-2972) funded by The Regional Government of 
Madrid. Thanks to Madrid City Council for collaborating in the development of the project. The authors are also grateful to 
Extremadura Research Center for Advanced Technologies (CETA-CIEMAT) by helping in using its computing facilities for the 
simulations. CETA-CIEMAT belongs to CIEMAT and the Government of Spain and is funded by the European Regional 
Development Fund.
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CFD modelling of particle matter dispersion in a real hot-spot

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CFD modelling of particle matter dispersion in a real hot-spot

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